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Massachusetts Institute of Technology

Optimization of blended battery packs

Abstract

dc:description.abstract

This thesis reviews the traditional battery pack design process for hybrid and electric vehicles, and presents a dynamic programming (DP) based algorithm that eases the process of cell selection and pack design, especially for blended battery packs (those containing two or more different energy sources). The proposed algorithm simultaneously optimizes the size of the battery pack while determining the ideal control strategy for the power split between the two sources. To test the algorithm, a simulation experiment is presented that compares the results of the DP based algorithm with single energy source options and a peak shaving heuristic strategy. The results of this experiment show that the algorithm reliably picks the lowest cost solution, and illustrates that blended battery packs have great potential for cost reduction in hybrid vehicles.

Degree

thesis:*
Department dc:contributor.department
Massachusetts Institute of Technology. Department of Mechanical Engineering.
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2013

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Erb, Dylan C. (Dylan Charles)
Advisor dc:contributor.advisor
  • Sanjay E. Sarma.

Subjects

dc:subject × 1

Rights

dc:rights
Statement dc:rights
  • M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
Language dc:language.iso
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/1721.1/81601
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/81601

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Erb, Dylan C. (Dylan Charles). Optimization of blended battery packs. Massachusetts Institute of Technology, 2013. http://hdl.handle.net/1721.1/81601